Hand Gesture Recognition Using Appearance Features Based on 3D Point Cloud

Chong, Yanwen; Huang, Jianfeng; Pan, Shaoming

doi:10.4236/jsea.2016.94009

Cited by 15 publications

(6 citation statements)

References 9 publications

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“…Currently, research work is going on 3-D image data which includes depth information [16] for gesture processing with various use of depth cameras such as leap motion controller [17], Kinect sensor [18] and so on. The future work will be concentrate on ISL symbols and sentences which will include the language processing engine with depth sensors.…”

Section: Discussionmentioning

confidence: 99%

Vision Based Hand Gesture Recognition Using Fourier Descriptor for Indian Sign Language

Ghotkar¹,

Vidap²,

Ghotkar³

2016

SIPIJ

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Indian Sign Language (ISL) interpretation is the major research work going on to aid Indian deaf and dumb people. Considering the limitation of glove/sensor based approach, vision based approach was considered for ISL interpretation system. Among different human modalities, hand is the primarily used modality to any sign language interpretation system so, hand gesture was used for recognition of manual alphabets and numbers. ISL consists of manual alphabets, numbers as well as large set of vocabulary with grammar. In this paper, methodology for recognition of static ISL manual alphabets, number and static symbols is given. ISL alphabet consists of single handed and two handed sign. Fourier descriptor as a feature extraction method was chosen due the property of invariant to rotation, scale and translation. True positive rate was achieved 94.15% using nearest neighbourhood classifier with Euclidean distance where sample data were considered with different illumination changes, different skin color and varying distance from camera to signer position.

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Section: Discussionmentioning

confidence: 99%

Vision Based Hand Gesture Recognition Using Fourier Descriptor for Indian Sign Language

Ghotkar¹,

Vidap²,

Ghotkar³

2016

SIPIJ

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“…The gesture is recorded with the help of the kinect sensor and the arduino is programmed in c language written in microsoft visual studio. Chong Y et al [7], depicts a method of detection of hand gestures on the basis of 3Dpoint cloud. Based on the depth camera firstly the raw data of the hand is extracted.…”

Section: Literature Reviewmentioning

confidence: 99%

“…As a result, many studies have been conducted on gesture technology and its potential capabilities in numerous disciplines, making it an appealing tool for humans.The Hand gesture applications for the interaction between computer and human are now being researched in depth. Users may operate devices without touching anything, such as a panel, keyboard, or mouse, with these applications [6][7], Users only have to face the camera and raise their hands to manage the devices. Hand gestures are the easiest to use and most convenient for communicating among the numerous sorts of gestures.…”

Section: Introductionmentioning

confidence: 99%

Gesture Controlled Mobile Robot with the Collaboration of MATLAB and PROTEUS

Revoo

Giri

Anand

2022

Advances in Transdisciplinary Engineering

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Gesture recognition is a type of technology that can be used to control robots, manipulators, and other devices. Human-Computer Interaction (HCI) and research into creating simple-to-use interfaces by utilising natural communication have gotten a lot of press recently, as have human manipulation skills. When using gesture recognition, the user who is making the gesture is not necessary to wear any equipment or gadgets on their body. A camera linked to a device reads the body’s gestures and produces an output. The major purpose of this paper is to use MATLAB to control motor direction in proteus while also combining both software with VSPE (visual serial port emulator). Before immediately implementing this method on a robot, we can first simulate the outcomes to improve accuracy or correct models.

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“…The second approach is the use of image sensors [22][23][24] or cameras to obtain the commands from hand gestures [25]; the sensors are trained on image features which include color, shape, texture, position contours, and motion of the hands. Our proposed model is based on the second approach and recognizes the hand gestures using imagery sensors or cameras [26].…”

Section: Introductionmentioning

confidence: 99%

“…At last, a multilayer perceptron was used to classify the four-hand gestures, i.e., ready, swing, on/speedup & off. [26] The model consists of a few steps. The hand gestures were captured using the web camera and were then preprocessed to detect the hands.…”

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confidence: 99%

Dynamic Hand Gesture Recognition for Smart Lifecare Routines via K-Ary Tree Hashing Classifier

et al. 2022

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In the past few years, home appliances have been influenced by the latest technologies and changes in consumer trends. One of the most desired gadgets of this time is a universal remote control for gestures. Hand gestures are the best way to control home appliances. This paper presents a novel method of recognizing hand gestures for smart home appliances using imaging sensors. The proposed model is divided into six steps. First, preprocessing is done to de-noise the video frames and resize each frame to a specific dimension. Second, the hand is detected using a single shot detector-based convolution neural network (SSD-CNN) model. Third, landmarks are localized on the hand using the skeleton method. Fourth, features are extracted based on point-based trajectories, frame differencing, orientation histograms, and 3D point clouds. Fifth, features are optimized using fuzzy logic, and last, the H-Hash classifier is used for the classification of hand gestures. The system is tested on two benchmark datasets, namely, the IPN hand dataset and Jester dataset. The recognition accuracy on the IPN hand dataset is 88.46% and on Jester datasets is 87.69%. Users can control their smart home appliances, such as television, radio, air conditioner, and vacuum cleaner, using the proposed system.

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Hand Gesture Recognition Using Appearance Features Based on 3D Point Cloud

Cited by 15 publications

References 9 publications

Vision Based Hand Gesture Recognition Using Fourier Descriptor for Indian Sign Language

Vision Based Hand Gesture Recognition Using Fourier Descriptor for Indian Sign Language

Gesture Controlled Mobile Robot with the Collaboration of MATLAB and PROTEUS

Dynamic Hand Gesture Recognition for Smart Lifecare Routines via K-Ary Tree Hashing Classifier

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